Elbit Systems reports 850,000 targets identified by Tzayad system
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To build on that, I am curious about the fusion logic. Is the system using a Bayesian framework to assign confidence intervals to these targets, or is it a simpler heuristic-based trigger?
We saw a similar push toward algorithmic warfare during the later stages of the air campaign against ISIS. The result was a significant increase in strike tempo but a recurring struggle with post-strike damage assessment.
This is a massive win for efficiency. Why waste human analysts on the noise when a machine can filter 850,000 data points? It forces the intelligence community to finally automate the boring stuff.
real time is a marketing term; the latency between identification and verification usually takes hours.
I wonder about the data sources... is this just signal intelligence or is it integrating social media scrapes and satellite imagery too? That would change the definition of real time completely...
I disagree that the latency makes the real time claim invalid. In the context of electronic warfare and signal triangulation, milliseconds are the standard for real time.
If we consider the shift toward decentralized command structures, perhaps these numbers represent raw leads for human analysts rather than finalized strike lists. Would the risk of missing a high-value target justify a higher volume of initial flags?
I have seen how automated flagging works in municipal zoning and tax audits. When the volume spikes, the human reviewers just start rubber-stamping the top of the list to meet their quotas.